Teaching Multiplicative Thinking With Virtual Representations to Children With Mathematics Difficulty

Abstract

Whole number computations are a critical skill that serves as a foundation upon which higher-order concepts in mathematics are taught to children. To facilitate their instruction, educators often use multiple representations to support a child’s cognition. Representations with physical manipulatives are widely studied through a graduated instructional sequence featuring concrete, representational, and abstract stages of learning. In contrast, research on representational sequences featuring virtual manipulatives is less robust. Thus, this study evaluated an instructional strategy with virtual manipulatives, static representational drawings, and abstract algorithms to teach multiplication to three elementary students with mathematics difficulty. A functional relation was established via a single-subject multiple probe design between the treatment and students’ accuracy performance. Baseline-corrected Tau estimates confirmed a medium effect size for all three students, while student performance on measures assessing the number of errors committed and the duration of sessions also returned favorable findings.